• Journal of the Institute of Convergence Signal Processing
• /
• v.7 no.2
• /
• pp.53-59
• /
• 2006

Dynamic neural networks have been applied to diverse fields requiring temporal signal processing such as system identification and signal prediction. This paper proposes the gamma neural network(GAM), which uses gamma memory kernel in the hidden layer of feedforward multilayered network, to improve dynamics of networks and then describes nonlinear adaptive prediction using the proposed network as an adaptive filter. The proposed network is evaluated in nonlinear signal prediction and compared with feedforword(FNN) and recurrent neural networks(RNN) for the relative comparison of prediction performance. Simulation results show that the GAM network performs better with respect to the convergence speed and prediction accuracy, indicating that it can be a more effective prediction model than conventional multilayered networks in nonlinear prediction for nonstationary signals.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.10
• /
• pp.1479-1485
• /
• 2015

Robot's technology was very simple and repetitive in the past. Nowadays, robots are required to perform intelligent operation. So, path planning has been studied extensively to create a path from start position to the goal position. In this paper, potential field algorithm was used for path planning in dynamic environments. It is used for a path plan of mobile robot because it is elegant mathematical analysis and simplicity. However, there are some problems. The problems are collision risk, avoidance path, time attrition. In order to resolve path problems, we amalgamated potential field algorithm with the artificial neural network system. The input of the neural network system is set using relative velocity and location between the robot and the obstacle. The output of the neural network system is used for the weighting factor of the repulsive potential function. The potential field algorithm problem of mobile robot's path planning can be improved by using artificial neural network system. The suggested algorithm was verified by simulations in various dynamic environments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.9
• /
• pp.3034-3055
• /
• 2014

Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.

• Journal of Information Processing Systems
• /
• v.17 no.3
• /
• pp.556-570
• /
• 2021

The existing video expression recognition methods mainly focus on the spatial feature extraction of video expression images, but tend to ignore the dynamic features of video sequences. To solve this problem, a multi-mode convolution neural network method is proposed to effectively improve the performance of facial expression recognition in video. Firstly, OpenFace 2.0 is used to detect face images in video, and two deep convolution neural networks are used to extract spatiotemporal expression features. Furthermore, spatial convolution neural network is used to extract the spatial information features of each static expression image, and the dynamic information feature is extracted from the optical flow information of multiple expression images based on temporal convolution neural network. Then, the spatiotemporal features learned by the two deep convolution neural networks are fused by multiplication. Finally, the fused features are input into support vector machine to realize the facial expression classification. Experimental results show that the recognition accuracy of the proposed method can reach 64.57% and 60.89%, respectively on RML and Baum-ls datasets. It is better than that of other contrast methods.

• Journal of KIISE:Information Networking
• /
• v.28 no.3
• /
• pp.406-416
• /
• 2001

Single path routing schemes using dynamic routing metric amy find out the dynamic network status and recompute paths to keep the traffic from the highly loaded regions of the network. This type of routing approach, however, may lead to a routing oscillation, and further, it cannot exploit multi-paths that may frequently exist in the real network. We propose a multipath routing scheme with dynamic load balancing, called MP-DLB, which is capable of reducing the overhead incurred by the multipath routing with dynamic load balancing approach while taking advantage of the high routing performance provided by the approach. According to the analysis of Internet packet traces which show that a high percentage of network traffic is destined for a small number of networks, MP-DLB applies the multipath routing with dynamic load balancing only to a limited subset of all the destinations in the network. For the rest of the destinations, it applies traditional single path routing scheme. This approach may reduce overall routing overheads by limiting the number of destinations to apply the more complicated routing scheme while it can keep the routing performance high by providing efficient routing for the most significant traffic in the routing performance. A series of simulations are done to analyze the performance of MP-DLB. The simulation results show that MP-DLB may effectively cope with the congestion and achieve high routing performance by distributing traffic streams that are generated from varying sources and heading toward a specific hot destination over multi-paths.

• Journal of KIISE:Software and Applications
• /
• v.31 no.8
• /
• pp.1073-1082
• /
• 2004

This paper presents a technique for an agent to adaptively behave to unforeseen and dynamic circumstances. Since the traditional methods utilized the information about an environment to control intelligent agents, they were robust but could not behave adaptively in a complex and dynamic world. A behavior-based method is suitable for generating adaptive behaviors within environments, but it is necessary to devise a hybrid control architecture that incorporates the capabilities of inference, learning and planning for high-level abstract behaviors. This Paper proposes a 2-level control architecture for generating adaptive behaviors to perceive and avoid dynamic moving obstacles as well as static obstacles. The first level is behavior-network for generating reflexive and autonomous behaviors, and the second level is to infer dynamic situation of agents. Through simulation, it has been confirmed that the agent reaches a goal point while avoiding static and moving obstacles with the proposed method.

• Journal of KIISE:Software and Applications
• /
• v.35 no.4
• /
• pp.265-279
• /
• 2008

The idea of using hand gestures for human-computer interaction is not new and has been studied intensively during the last dorado with a significant amount of qualitative progress that, however, has been short of our expectations. This paper describes a dynamic Bayesian network or DBN based approach to both two-hand gestures and one-hand gestures. Unlike wired glove-based approaches, the success of camera-based methods depends greatly on the image processing and feature extraction results. So the proposed method of DBN-based inference is preceded by fail-safe steps of skin extraction and modeling, and motion tracking. Then a new gesture recognition model for a set of both one-hand and two-hand gestures is proposed based on the dynamic Bayesian network framework which makes it easy to represent the relationship among features and incorporate new information to a model. In an experiment with ten isolated gestures, we obtained the recognition rate upwards of 99.59% with cross validation. The proposed model and the related approach are believed to have a strong potential for successful applications to other related problems such as sign languages.

• Journal of Information Processing Systems
• /
• v.6 no.3
• /
• pp.269-294
• /
• 2010

The interconnection of mobile devices in urban environments can open up a lot of vistas for collaboration and content-based services. This will require setting up of a network in an urban environment which not only provides the necessary services to the user but also ensures that the network is secure and energy efficient. In this paper, we propose a secure, energy efficient dynamic routing protocol for heterogeneous wireless sensor networks in urban environments. A decision is made by every node based on various parameters like longevity, distance, battery power which measure the node and link quality to decide the next hop in the route. This ensures that the total load is distributed evenly while conserving the energy of battery-constrained nodes. The protocol also maintains a trusted population for each node through Dynamic Trust Factor (DTF) which ensures secure communication in the environment by gradually isolating the malicious nodes. The results obtained show that the proposed protocol when compared with another energy efficient protocol (MMBCR) and a widely accepted protocol (DSR) gives far better results in terms of energy efficiency. Similarly, it also outdoes a secure protocol (QDV) when it comes to detecting malicious nodes in the network.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.23 no.6
• /
• pp.1025-1035
• /
• 2013

There has been an explosive increase in the population of OSN(online social network) for 10 years. OSN provides users with many opportunities to have communication among friends, families and goes so far as to make relationships among unknown people having similar belief or interest. However, OSN also produced adverse effects such as privacy breaches, leaking uncontrolled information or disseminating false information. Access control models such as MAC, DAC, RBAC are applied to the OSN to control those problems but those models in OSN are not fit in dynamic OSN environment because user's acts in OSN are unpredictable and static access control imposes burden on users to change access control rules one by one. This paper proposes the dynamic trust-based access control to solve the problems of traditional static access control in OSN.

• Journal of the Korea Convergence Society
• /
• v.11 no.9
• /
• pp.21-29
• /
• 2020

The Topic Modeling research, the methodology for deduction keyword within literature, has become active with the explosion of data from digital society transition. The research objective is to investigate research trends in D.N.A.(Data, Network, Artificial Intelligence) field using DTM(Dynamic Topic Model). DTM model was applied to the 1,519 of research projects with SW·A.I technology classifications among ICT(Information and Communication Technology) field projects between 6 years(2015~2020). As a result, technology keyword for D.N.A. field; Big data, Cloud, Artificial Intelligence, extended keyword; Unstructured, Edge Computing, Learning, Recognition was appeared every year, and accordingly that the above technology is being researched inclusively from other projects can be inferred. Finally, it is expected that the result from this paper become useful for future policy·R&D planning and corporation's technology·marketing strategy.